Mid Sweden University

Caffeine enhances endurance performance but may impair shooting accuracy, creating a potential trade-off for overall biathlon performance. In a randomized, placebo-controlled, crossover study, seven elite male biathletes consumed caffeine (3 mg/kg) or taste-matched placebo 60 min before a simulated biathlon competition consisting of five "laps" of 6-min treadmill skiing interspersed by four five-shot bouts. Participants further performed precision shooting (20 prone and 20 standing) pre- and postcompetition. Caffeine increased distance covered in Laps 1 (1,824 +/- 73 vs. 1,772 +/- 66 m; p = .03, dz = 1.12) and 2 (1,801 +/- 92 vs. 1,776 +/- 84 m; p = .02, dz = 1.19) but did not improve total distance (p = .06). Blood lactate (p = .01, eta(2)(p)=.85) and ventilation (p < .001, eta(2)(p)=.90) increased with caffeine. Heart rate (p = .07) and perceived exertion (p = .69) did not differ between conditions. Caffeine impaired shooting accuracy in standing (72.9 +/- 16.0% vs. 82.9 +/- 7.6%; p = .03, dz = 0.87), but not prone. Integrated race times did not differ between conditions for individual (71.72 +/- 5.27 vs. 71.58 +/- 4.57 min), mass start (52.45 +/- 3.67 vs. 52.57 +/- 3.27 min), or pursuit (44.18 +/- 3.18 vs. 44.23 +/- 2.83 min; all p > .77) formats. Caffeine impaired postexercise precision shooting in prone position (88.9 +/- 6.0% vs. 93.3 +/- 7.5%; p = .04, dz = 0.65). Our findings highlight task-specific effects of caffeine, emphasizing the importance of tailoring supplementation to integrated performance demands.

Purpose: Performance analyses in cross-country skiing often focus on lap or terrain-level splits. However, few studies have explored micro-pacing strategies—particularly in Skiathlon, an Olympic event requiring athletes to complete both classical and freestyle techniques on the same course. Methods: Thirteen national-level male skiers were tracked during an International Ski Federation-certified Skiathlon using GNSS and trunk-mounted sensors. Instantaneous speed profiles were analysed using one-dimensional statistical parametric mapping (SPM) to identify “race-critical clusters”: contiguous intervals where speed significantly predicted section time (α = 0.05) across all eight laps (four classical, four freestyle). Results: Freestyle laps were 4% faster than classical, with greater terrain-specific speed differences and pacing variability in classical, especially downhills. Seven race-critical clusters were identified: two uphill, four downhill, and one flat. These accounted for 11.3 s (classic) and 10.9 s (freestyle) of the time gap between the fast and slow group. In these segments, faster skiers used higher-gear sub-techniques and exhibited longer cycle lengths and/or higher frequencies (p < 0.05). Conclusions: Within race-critical clusters, the faster skiers gained substantial time advantages. Secondary analyses showed clear differences in sub-technique selection and kinematic profiles, suggesting that technical execution plays a critical role in these performance gains. Athletes and coaches may consider integrating GNSS-based tracking, SPM, and wearable-derived technique analysis into race evaluation to move beyond traditional split times and focus training on the most decisive segments of the course. 

PlayerLoad™ is the most widely used accelerometer-derived metric for quantifying external demands in sport. Its normalized variant, PlayerLoad·min−1, is also commonly used as a marker of exercise intensity. However, recent literature has raised concerns regarding its scientific foundation, including inconsistent definitions, arbitrary units, opaque filtering methods, questionable theoretical underpinnings, and imprecise mechanical terminology. The construct validity of PlayerLoad™ remains unverified, and emerging evidence suggests weak dose–response relationships with performance outcomes. Although widely adopted in practice, these concerns warrant critical scientific scrutiny. This review critically evaluates the validity and reliability of the PlayerLoad™ metric, highlighting the need for greater transparency and theoretical rigor in wearable athlete monitoring. Furthermore, we present alternative accelerometer-derived metrics, developed from clearer biomechanical and physiological principles, which may offer more robust and interpretable measures for researchers and practitioners. 

Background Physical activity is essential for health and well-being during adolescence, and active behaviour early in life predicts higher physical activity levels in adulthood. Although adolescents with intellectual disability (ID) consistently show lower activity levels than peers without ID, national environments—such as school structures, disability support systems, and access to inclusive leisure activities—may influence these patterns. There is limited evidence from Sweden, a country with distinct educational and support frameworks for youth with ID. The present study aimed to examine physical activity patterns among Swedish adolescents with and without ID using accelerometer data. Methods Physical activity was measured objectively using hip-worn accelerometers (ActiGraph GT3X) over seven consecutive days. This cross-sectional study included 45 adolescents with mild-to-moderate ID (median [IQR], 17.0 [14.0–19.0] years; 45.2% females) and 70 adolescents without ID (16.0 [15.0-16.3] years; 62.2% females). Physical activity was categorised as sedentary behaviour (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) and analysed across school days, weekend days, and separately for daytime and evening periods on school days. Results Overall, the relative amount of SB was similar between groups (p > 0.05), but significant differences were observed for LPA and MVPA. Adolescents with ID accumulated more LPA during school-day daytime hours (23% vs. 19%; p = 0.012), while peers without ID accumulated more MVPA during leisure time, such as school-day evenings (p = 0.025) and weekends (p = 0.039). For both groups, MVPA was higher on school days than on weekends (p < 0.001). Among adolescents with ID, SB increased markedly on weekends (72% vs. 77%; p < 0.001). Conclusion Adolescents with ID were generally less physically active than peers without ID, except during schoolday daytime, where the MVPA was similar and LPA was higher. Leisure time, particularly weekends and schoolday evenings, seems to be a critical period in achieving sufficient MVPA among adolescents with ID. Targeted interventions and coordinated support from key stakeholders such as school health services, paediatric health care, social care services and organised sports, with a particular focus on unstructured time, may help promote active lifestyles and reduce health disparities in this population.

Purpose

Biathlon is an endurance sport that combines high-intensity cross-country skiing with precision shooting, requiring athletes to carry a rifle while skiing. This study examined the effect of rifle carriage on angular kinematics involving hip and knee range of motion (ROM) in on-snow biathlon skiing.

Methods

29 tier 3 level biathletes (11 F; 18 M) skied two maximal effort time trials (2300 m), once with and once without carrying the biathlon rifle. A 3D motion analysis system, comprising of twelve inertial measurement units, was used to measure hip and knee ROM in the sagittal plane. Multilevel linear models, considering slope, stance (dominant/non-dominant), and side (leading/lagging, left/right), were employed to analyze the effects of rifle carriage on knee and hip ROM in gears 2 and 3.

Results

In gear 2, rifle carriage was associated with reduced knee (p < .001) and hip ROM.

(p < .001). In gear 3, rifle carriage was associated with reduced knee ROM (p < .001) but greater hip ROM (p = .003).

Conclusion

Biathletes change their skiing kinematics when carrying a rifle during on-snow skiing. Rifle carriage was associated with decreased knee and hip ROM in gear 2, and reduced knee but increased hip ROM in gear 3. Future research should determine the relationships between rifle-induced changes to skiing kinematics with performance.

Purpose: This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how KDE plots, alongside traditional training metrics, might provide a more detailed understanding of heart rate (HR) intensity patterns, aiding in the evaluation of training quality and compliance.

Methods: Fifteen elite-level youth biathletes from two national academy programmes were monitored over 5–6 weeks using HR monitors. Training sessions were measured via time-in-zone (TIZ) within a five-zone HR model with any time accumulated below the threshold for Zone 1, considered Zone 0. Sessions were dichotomised into those planned as low-intensity training (LIT) or those planned with high-intensity training (HIT). KDE analyses were conducted in MATLAB (Version R2020b) using the “ksdensity” function to create 2D KDE plots that visualise HR intensity accumulation across each programme, session type (e.g., Low-intensity training: LIT; High-intensity training: HIT), and individual athlete responses. Traditional histogram plots and grouped bar charts were also used for comparison.

Results: For LIT sessions, athletes performed less time in Zone 1 than planned, while performed time exceeded planned time in Zone 2. For HIT sessions, performed time in Zone 5 was lower than planned. All sessions contained unplanned time in Zone 0. The 2D KDE plots provided a continuous and detailed representation of HR intensity accumulation throughout training sessions, revealing patterns and intensity fluctuations that complement traditional TIZ analyses.

Conclusions: 2D KDE plots might serve as a valuable complementary tool for assessing TID in biathlon, offering a more nuanced and continuous view of HR intensity. By identifying discrepancies between planned and performed training intensity, coaches can refine strategies and provide individualised feedback. Incorporating KDE plots into training monitoring could improve training alignment, helping reduce overtraining or undertraining risks and optimising athlete development.

Sensor technology is often used across many sports by coaches, practitioners, and researchers. The wide range of sensors and numerous possibilities can be both interesting and daunting. Here, we explore the use of sensor technologies, focusing on Global Navigation Satellite Systems, Inertial Measurement Units, and heart rate monitoring for analyses of Para-Nordic skiing. We discuss current applications and future possibilities as well as some challenges and limitations. For example, we discuss what we may learn from analyses of skiing speed or sub-technique selection throughout a racecourse. We also offer ideas for how coaches, practitioners, and researchers can use these sensors in their work to further both the understanding and performance of Para-Nordic skiing. 

This study aimed to optimise performance prediction in short-course swimming through Principal Component Analyses (PCA) and multiple regression. All women’s freestyle races at the European Short-Course Swimming Championships were analysed. Established performance metrics were obtained including start, free-swimming, and turn performance metrics. PCA were conducted to reduce redundant variables, and a multiple linear regression was performed where the criterion was swimming time. A practical tool, the Potential Predictor, was developed from regression equations to facilitate performance prediction. Bland and Altman analyses with 95% limits of agreement (95% LOA) were used to assess agreement between predicted and actual swimming performance. There was a very strong agreement between predicted and actual swimming performance. The mean bias for all race distances was less than 0.1s with wider LOAs for the 800 m (95% LOA −7.6 to + 7.7s) but tighter LOAs for the other races (95% LOAs −0.6 to + 0.6s). Free-Swimming Speed (FSS) and turn performance were identified as Key Performance Indicators (KPIs) in the longer distance races (200 m, 400 m, 800 m). Start performance emerged as a KPI in sprint races (50 m and 100 m). The successful implementation of PCA and multiple regression provides coaches with a valuable tool to uncover individual potential and empowers data-driven decision-making in athlete training. 

This study compared performance strategies and sub-technique selection in cross-country skate skiing sprint races, specifically individual time-trial (ITT) and head-to-head (H2H) formats. Fourteen male cross-country skiers from the Chinese national team participated in the FIS-sanctioned sprint race day. GNSS and heart rate sensors recorded positioning, skiing speeds, heart rate, sub-technique usage, and skiing kinematics. Statistical parametric mapping (SPM) was used to determine the course positions (clusters) where instantaneous skiing speed was significantly associated with section time. One-way analyses of variance were used to examine differences between the ITT and H2H. H2H race speeds were 2.4 +/- 0.2% faster than the ITT race (p < 0.05).Variations in sub-technique and skiing kinematics were observed between race formats, indicating different strategies and tactics employed by athletes. SPM identified specific clusters (primarily uphill) where the fastest athlete gained significant time over the slowest. The greatest time gains were associated with higher G3 sub-technique usage and longer G3 cycle length on steep uphill terrain (9-13% gradients). Integrating SPM analyses and sub-technique assessments can help optimise performance and tactics in sprint races. This study enhances our understanding of cross-country skiing dynamics and performance variations among elite competitors.

Purpose To examine the micro-pacing (within-lap) strategies during biathlon skiing with and without the biathlon rifle. Methods Twenty biathletes (7 women, 13 men) performed two crosscountry skiing time-trials on a ≈2300 m course, once with and once without the biathlon rifle. During time-trials, biathletes wore a sensor that recorded position, distance and skiing-speed. A trajectory correction and statistical parametric mapping procedure determined the course positions (clusters) where instantaneous skiing-speed was significantly related to time-trial performance. The time differences between the fastest and slowest skier in these clusters were calculated. Results The fastest biathletes skied with greater instantaneous speeds in specific clusters, which included both uphill and downhill sections. The clusters represented time gains for the fastest skier over the slowest skier of between 16.1 and 25.8 s for the women and between 18.9 and 21.9 s for the men. The largest time gains between the fastest and slowest biathletes were observed in a downhill section that was preceded by a 180° turn, where time gains were between 2.9 and 4.1 s in clusters of between just 12 to 62 m. In biathlon skiing with-rifle, there were more clusters that were not present during without-rifle. When skiing with-rifle, there were additional clusters in the uphill sections that represented time gains of 5.2 s and 2.3 s for the women and men, respectively. Conclusions Statistical parametric mapping can be used in biathlon to provide pacing and performance feedback to athletes and coaches.